Evidence map›Paper›PMID 24883271›Full record

ArticleArchives of plastic surgery2014

Research priorities in light of current trends in microsurgical training: revalidation, simulation, cross-training, and standardisation.

Rebecca Spenser Nicholas, Rudo N Madada-Nyakauru, Renu Anita Irri, Simon Richard Myers, Ali Mahmoud Ghanem

Abstract read
In one paragraph

Article in Archives of plastic surgery, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Rebecca Spenser NicholasDepartment of Plastic Surgery, Royal London Hospital, London, UK.
Rudo N Madada-NyakauruImperial College London, London, UK.
Renu Anita IrriImperial College London, London, UK.
Simon Richard MyersAcademic Plastic Surgery Group, Barts and the London School of Medicine and Dentistry, London, UK.
Ali Mahmoud GhanemAcademic Plastic Surgery Group, Barts and the London School of Medicine and Dentistry, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plastic surgery training worldwide has seen a thorough restructuring over the past decade, with the introduction of formal training curricula and work-based assessment tools. Part of this process has been the introduction of revalidation and a greater use of simulation in training delivery. Simulation is an increasingly important tool for educators because it provides a way to reduce risks to both trainees and patients, whilst facilitating improved technical proficiency. Current microsurgery training interventions are often predicated on theories of skill acquisition and development that follow a 'practice makes perfect' model. Given the changing landscape of surgical training and advances in educational theories related to skill development, research is needed to assess the potential benefits of alternative models, particularly cross-training, a model now widely used in non-medical areas with significant benefits. Furthermore, with the proliferation of microsurgery training interventions and therefore diversity in length, cost, content and models used, appropriate standardisation will be an important factor to ensure that courses deliver consistent and effective training that achieves appropriate levels of competency. Key research requirements should be gathered and used in directing further research in these areas to achieve on-going improvement of microsurgery training.

Indexed as

EducationInservice trainingMicrosurgeryPatient simulationSurgery, plastic

Identifiers

PMID24883271
PMCPMC4037766

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.